PyViennaCL: Python wrapper for GPU-accelerated linear algebra

February 26th, 2014

The new free open-source PyViennaCL 1.0.0 release provides the Python bindings for the ViennaCL linear algebra and numerical computation library for GPGPU and heterogeneous systems. ViennaCL itself is a header-only C++ library, so these bindings make available to Python programmers ViennaCL’s fast OpenCL and CUDA algorithms, in a way that is idiomatic and compatible with the Python community’s most popular scientific packages, NumPy and SciPy. Support through the Google Summer of Code 2013 for the primary developer Toby St Clere Smithe is greatly appreciated.

More information and download: PyViennaCL Home

Webinar: Accelerating Full Waveform Inversion via OpenCL on AMD GPUs

February 26th, 2014

On March 5 at 11:00am (PST), Acceleware hosts a webinar on accelerating a seismic algorithm on a cluster of AMD GPU compute nodes. The presentation will begin with an outline of the full waveform inversion (FWI) algorithm, followed by an introduction to OpenCL. The OpenCL programming model and memory spaces will be introduced. Strategies for formulating the problem to take advantage of the massively parallel GPU architecture, and key optimizations techniques are discussed including coalescing and an iterative approach to handle the slices. Performance results for the GPU are compared to the CPU run times. Click here to register.

CfP: High-Performance Graphics

February 17th, 2014

High-Performance Graphics is the leading international forum for performance-oriented graphics and imaging systems research including innovative algorithms, efficient implementations, languages, parallelism, compilers, parallelism, hardware and architectures for high-performance graphics. High-Performance Graphics was founded in 2009, synthesizing multiple conferences to bring together researchers, engineers, and architects to discuss the complex interactions of parallel hardware, novel programming models, and efficient algorithms in the design of systems for current and future graphics and visual computing applications.

HPC is co-located with EGSR, in Lyon, France, June 23-25, 2014. More information:

CfP: ADBIS workshop on GPUs In Databases GID 2014

February 17th, 2014

High performance of modern Graphics Processing Units may be utilized not only for graphics related application but also for general computing. This computing power has been utilized in new variants of many algorithms from almost every computer science domain. Unfortunately, while other application domains strongly benefit from utilizing the GPUs, databases related applications seem not to get enough attention. The main goal of GPUs in Databases workshop is to fill this gap. This event is devoted to sharing the knowledge related to applying GPUs in Database environments and to discuss possible future development of this application domain.

ADBIS workshop on GPUs In Databases GID 2014, September 7th, 2014, Ohrid, Republic of Macedonia. More information:

Maximizing Shared Memory Bandwidth on NVIDIA Kepler GPUs

February 17th, 2014

This tutorial by Dan Cyca outlines the shared memory configurations for NVIDIA Fermi and Kepler architectures, and demonstrates how to rewrite kernels to take advantage of the changes in Kepler’s shared memory architecture.

OpenCLIPP: an OpenCL library for optimized image processing primitives

February 2nd, 2014

OpenCLIPP is a library providing processing primitives (image processing primitives in the first version) implemented with OpenCL for fast execution on dedicated computing devices like GPUs. Two interfaces are provided: C (similar to the Intel IPP and NVIDIA NPP libraries) and C++. OpenCLIPP is free for personal and commercial use. It can be downloaded from GitHub.

Related publication:
M. Akhloufi, A. Campagna, “OpenCLIPP: OpenCL Integrated Performance Primitives library for computer vision applications”, Proc. SPIE Electronic Imaging 2014, Intelligent Robots and Computer Vision XXXI: Algorithms and Techniques, P. 9025-31, February 2014.

Acceleware CUDA Training Feb 25-28, 2014

January 15th, 2014

Developed in partnership with NVIDIA, this hands-on four day course will teach how to write and optimize applications that fully leverage the multi-core processing capabilities of the GPU. Benefits include:

  • Hands-on exercises and progressive lectures
  • Individual laptops equipped with NVIDIA GPUs for student use
  • Small class sizes to maximize learning
  • 90 days post training support – NEW!

February 25-28, 2014, Baltimore, MD, USA, details and registration.

Webinar: HOOMD-blue for Polymer Simulations and Big Systems

January 15th, 2014

This webinar will demonstrate how real-world computational research in soft matter physics can be accelerated on a GPU-equipped desktop computer with the HOOMD-blue molecular dynamics software. A presentation of how to set up a simulation of a dense polymer liquid, and how to analyze and visualize the results is provided. There will be a demonstration of how self-assembled ordered structures of block copolymers emerge out of an initially disordered configuration. With external potentials, an artificially ordered phase can be produced as well. HOOMD-blue’s easy-to-use scripting interface and plug-ins are used to create a productive work-flow and extend its capabilities. As an advanced topic, there will be a discussion of how the upcoming version of HOOMD-blue can be used on compute clusters running on ten to hundreds of GPUs in parallel, to boost simulations of long polymer chains or large-scale systems.

January 21, 2014, 11:00 a.m. EST, Registration required.

Javascript Library for GPGPU

December 30th, 2013

WebCLGL is a free Javascript library for general purpose computing using WebGL. It uses a code style like WebCL to handle the operations and then translate to WebGL code. The library is not 100% the same as the future WebCL specification nor has all its advantages, but it is already very usable.

Webinar: CUDA Tools for Optimal Performance and Productivity

December 30th, 2013

This webinar recording provides an overview of the profiling techniques and the tools available to help you optimize your code. It examines NVIDIA’s Visual Profiler and cuobjdump and highlight the various methods available for understanding the performance of CUDA program. The second part of the session focuses on debugging techniques and the tools available to help identify issues in kernels. The debugging tools provided in CUDA 5.5 including NSight and cuda-memcheck are discussed. The webinar recording can be accessed here.

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